Engineering, School of
https://hdl.handle.net/1842/3519
2020-02-18T03:30:37ZModelling the relative risk of large fires across the informal settlements of Cape Town
https://hdl.handle.net/1842/36775
Modelling the relative risk of large fires across the informal settlements of Cape Town
Stevens, Samuel
Home to an estimated 1 billion people globally, informal settlements are urban environments that are subject to a high risk of extensive fire spread. Their dense layouts and light, combustible building materials often facilitate the spread of fire through tens or hundreds of homes at once, rendering the inhabitants homeless. Tackling this issue requires a sound understanding of the many spatial factors which can contribute to fire spread. The aim of this study was to quantify the relative risk of large fires across informal settlements in Cape Town, South Africa – a city which has a notable history of devastating informal settlement fires. This was conducted primarily by developing a risk-scoring model based on fundamental fire dynamics and a survey of expert opinion on informal settlements. The study included a review of past disaster risk studies to aid the establishment of solid principles for the risk modelling method.
A ‘pairwise weighted’ risk model was developed, using GIS software to quantify the spatial environment. It showed a good degree of success in identifying settlements that have a history of severe fires, such as Masiphumelele, Imizamo Yethu and Kosovo, as being of very high fire risk. A particular advantage of the model is its ability to recognise three different categories of fire risk, imposed by infrastructural factors both within and external to a settlement, and environmental factors. However, the fire history data used as a metric to verify the accuracy of the model was unfortunately not of sufficient quality to facilitate a rigorous numerical validation of the model.
Fire risk mapping for informal settlements is a relatively new field of research, therefore many potential developments to the model were also proposed. The relationship between climate and informal settlement fire spread is currently poorly understood so it must be studied and adapted accordingly within the risk model. This could further contribute to modelling of seasonally variable fire risk. Furthermore, future methods for modelling risk directly from estimates of settlement density should be developed, to allow for automatic satellite image processing. This would be of great benefit as it would speed up the GIS-based data collation process which proved time consuming for this study.
2019-01-01T00:00:00ZHighway bridges in fire: characterisation of fire loading and structural behaviour
https://hdl.handle.net/1842/36773
Highway bridges in fire: characterisation of fire loading and structural behaviour
Hu, Jiayu
In bridge design, extreme hazards have been considered as design loads for
years, including wind, earthquake, snow, and floods; but fire hazard is not usually
considered in the design process. However, severe fire accidents occurring
near or under bridges are not as rare as generally perceived compared to
the other extreme hazards, especially earthquakes and floods. Therefore fire
resistance of bridges along the most critical arteries of transport networks, carrying
heavy traffic, should be considered. This should ideally be based upon
an estimation of the consequences of a particular level of bridge damage in
terms of social and economic costs.
Since there are no codes or standards relating to fire resistance of bridges,
assessment must rely upon a performance-based engineering approach. In
conducting performance-based studies of bridge fire resistance, most previous
researchers have used code-based fire curves, such as the ISO 834 standard
or Hydrocarbon fires, which assume uniform heating along the entire bridge
span. However, a real vehicle fire will naturally create a non-uniform, localised
fire under the bridge span and the hazard intensity will decay with distance
away from the burning vehicle. If such a scenario could be implemented in a
more realistic fire model, then more realistic thermal and thermo-mechanical
response of structures could be predicted, resulting in more reliable estimates
of performance.
This thesis consists of three main parts. Part I investigates the structural
performance of composite steel-framed bridges and the influence of bridge
shape on failure time under code-based Hydrocarbon fire loading. Part II uses
the CFD-based fire dynamics simulation code FDS to generate design fire
curves for four different classes of vehicles. The design fire curves include
the expected decay in the intensity of the heat flux due to the fire along the
bridge span. These curves were then generalised as mathematical functions
that can be easily used by engineers and designers in the assessment of the
performance of existing bridges under realistic hazard scenarios, for fire resistance
design. Rectangular bridge models were subjected to the most extreme
class of design fire (fuel tanker fires) in order to compare with the Hydrocarbon
fire. The analysis showed that, for the bridge structure considered, there is
no failure for the model in the fuel tanker fire scenario, even with conservative
assumptions. However, failure may occur if a higher heat release rate is used,
which is possible for large fuel tanker fires. In Part III the new design curves
(developed as mathematical functions) were implemented into the OpenSees
software framework to enable a seamless simulation from fire, to heat transfer
and structural response.
2020-02-02T00:00:00ZInvestigating the micromechanics of granular soils subjected to cyclic loading using discrete element method
https://hdl.handle.net/1842/36755
Investigating the micromechanics of granular soils subjected to cyclic loading using discrete element method
Keishing, Joel
he soil experiences millions of load cycle from nature, i.e., earthquake or many geo-engineering structures are subjected to cyclic loading during normal operation, e.g., renewable offshore wind turbines are likely to experience millions of load cycles, with variations in cycle magnitude and frequency, during their service lives. These forces are transmitted to the soil which may cause unacceptable soil displacement and, in extreme cases, it may lead to soil liquefaction. This is a major concern to geotechnical engineers, therefore determination of soil response to cyclic loading has great importance. This research investigates the undrained behaviour of sand subjected to monotonic and cyclic loading using DEM (Cundall and Strack, 1979). A series of constant-volume undrained simulations of sand subjected to monotonic loading at different initial stress ratio, confining pressure and void ratio were performed to gain the understanding of the monotonic behaviour of sand which is an essential precursor to the cyclic loading tests. One problem arises when shearing dense samples are the generation of unrealistically high stresses. Four alternatives are hypothesised to address the shortcomings of the constant-volume method are explored, each of which has a physical basis: particle crushing, the presence of highly compressible air within the sample, or the reduction of stiffness due to particle surface asperities or non-spherical particle shapes. In situations where a significant amount of particle crushing occurs, it is important to incorporate this in the simulations so that stresses are not over-estimated. In the absence of particle crushing, the most effective method to achieve more realistic stress–strain responses is to reduce the particle shear modulus substantially. This approach has the added computational benefit of enabling an increase in the simulation time-step. A Design of Experiments (DOE) approach was adopted to systematically investigate the behaviour of sand subjected to cyclic loading using DEM. Detailed simulations results are presented that related the influence of different parameters such as frequency, mean cyclic load, cyclic amplitude, confining pressure and void ratio on the dynamic properties of granular materials. Based on those DOE analyses, prediction of cyclic responses for randomly selected input parameters are presented. The void ratio was found to have the most significant effect on the shear modulus and coordination number of the sample. The influence of frequency on cyclic response quantities was found to be insignificant. In addition, energy terms were computed in a set of undrained cyclic triaxial discrete-element method simulations which form a parametric study of five factors: void ratio, initial mean effective stress, mean deviator stress, deviator stress amplitude and compressive/extensive initial loading. Void ratio is the only one of these factors which significantly affects the relationship between the excess pore water pressure and the unit energy. By increasing the void ratio or decreasing the initial mean effective stress, both the number of complete cycles and the energy dissipated per unit volume up to the onset of liquefaction, respectively denoted as Nl and δWd, were reduced. Initial stress anisotropy reduces Nl but increases δWd. Increasing the deviator stress amplitude also reduces Nl but has no significant effect on δWd. All of these observed trends in Nl and δWd match data from physical experiments, where available. The preferred contact orientation for frictional dissipation is between 30° and 40° for these cyclic simulations. There is a greater heterogeneity for extension than for compression, regardless of whether the initial phase of loading is compressive or extensive. Immediately following a shear reversal, the boundary work decreases and there is a period of negligible frictional dissipation which lasts for around 0.04% axial strain. If an energy-based model is being applied for liquefaction assessment of anisotropic samples, a significant improvement in the accuracy of the model may be achieved by including the mean deviator stress
2019-12-18T00:00:00ZModel-based reconstruction of accelerated quantitative magnetic resonance imaging (MRI)
https://hdl.handle.net/1842/36754
Model-based reconstruction of accelerated quantitative magnetic resonance imaging (MRI)
Bano, Wajiha
Quantitative MRI refers to the determination of quantitative parameters (T1,T2,diffusion, perfusion
etc.) in magnetic resonance imaging (MRI). The ’parameter maps’ are estimated from
a set of acquired MR images using a parameter model, i.e. a set of mathematical equations
that describes the MR images as a function of the parameter(s). A precise and accurate highresolution
estimation of the parameters is needed in order to detect small changes and/or to
visualize small structures. Particularly in clinical diagnostics, the method provides important
information about tissue structures and respective pathologic alterations. Unfortunately, it also
requires comparatively long measurement times which preclude widespread practical applications.
To overcome such limitations, approaches like Parallel Imaging (PI) and Compressed
Sensing (CS) along with the model-based reconstruction concept has been proposed. These
methods allow for the estimation of quantitative maps from only a fraction of the usually required
data.
The present work deals with the model-based reconstruction methods that are applicable for
the most widely available Cartesian (rectilinear) acquisition scheme. The initial implementation
was based on accelerating the T*2
mapping using Maximum Likelihood estimation and
Parallel Imaging (PI). The method was tested on a Multiecho Gradient Echo (MEGE) T*2
mapping
experiment in a phantom and a human brain with retrospective undersampling. Since
T*2
is very sensitive to phase perturbations as a result of magnetic field inhomogeneity further
work was done to address this. The importance of coherent phase information in improving
the accuracy of the accelerated T*2
mapping fitting was investigated. Using alternating minimization,
the method extends the MLE approach based on complex exponential model fitting
which avoids loss of phase information in recovering T*2 relaxation times. The implementation
of this method was tested on prospective(real time) undersampling in addition to retrospective.
Compared with fully sampled reference scans, the use of phase information reduced the error
of the accelerated T*2
maps by up to 20% as compared to baseline magnitude-only method. The total scan time for the four times accelerated 3D T*2
mapping was 7 minutes which is clinically acceptable. The second main part of this thesis focuses on the development of a model-based
super-resolution framework for the T2 mapping. 2D multi-echo spin-echo (MESE) acquisitions
suffer from low spatial resolution in the slice dimension. To overcome this limitation
while keeping acceptable scan times, we combined a classical super-resolution method with an
iterative model-based reconstruction to reconstruct T2 maps from highly undersampled MESE
data. Based on an optimal protocol determined from simulations, we were able to reconstruct
1mm3 isotropic T2 maps of both phantom and healthy volunteer data. Comparison of T2 values
obtained with the proposed method with fully sampled reference MESE results showed good
agreement. In summary, this thesis has introduced new approaches to employ signal models
in different applications, with the aim of either accelerating an acquisition, or improving the
accuracy of an existing method. These approaches may help to take the next step away from
qualitative towards a fully quantitative MR imaging modality, facilitating precision medicine
and personalized treatment.
2019-12-18T00:00:00Z